The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (27 page)

In the future, more and more careers will not be in pure information work—the kind that can be done entirely from a desk. Instead, they will include moving through and interacting with the physical world. This is because computers remain comparatively weak here, even as they get so much stronger at many cognitive tasks.

Advances like autonomous cars, drone airplanes, the Baxter robot, and hacked Kinect devices that can map a room show that great progress has been made in giving machines real-world capabilities, but a towel-folding robot illustrates how far we are from cracking Moravec’s paradox. A team of Berkeley researchers equipped a humanoid robot with four stereo cameras and algorithms that would allow it to ‘see’ towels, both individually and in piles. These algorithms worked; the robot successfully grasped and folded the towels, even though it sometimes took more than one try to grab them correctly. However, it took an average of 1,478 seconds, or more than twenty-four minutes, per towel. The robot spent most of that time looking to learn where the towel was and how to grasp it.
²¹

Results like these indicate that cooks, gardeners, repairmen, carpenters, dentists, and home health aides are not about to be replaced by machines in the short term. All of these professions involve a lot of sensorimotor work, and many of them also require the skills of ideation, large-frame pattern recognition, and complex communication. Not all of these jobs are well paying, but they’re also not subject to a head-to-head race against the machine.

They may, however, be subject to more competition among people. As the labor market polarizes more and the middle class continues to hollow out, people who were previously doing mid-skill knowledge work start going after jobs lower on the skill and wage ladder. After medical billing specialists have their work automated, for example, they may start looking for jobs as home health aides. This puts downward pressure on wages and makes it harder to find a job in that profession. Even if home health aides remain largely immune to automation, in short, they won’t necessarily be immune to all the effects of digitization.

The Fuzzy Future

We have to stress that none of our predictions and recommendations here should be treated as gospel. We don’t project that computers and robots are going to acquire the general skills of ideation, large-frame pattern recognition, and highly complex communication any time soon, and we don’t think that Moravec’s paradox is about to be fully resolved. But one thing we’ve learned about digital progress is
never say never
. Like many other observers, we’ve been surprised over and over as digital technologies demonstrated skills and abilities straight out of science fiction.

In fact, the boundary between uniquely human creativity and machine capabilities continues to change. Returning to the game of chess, back in 1956, thirteen-year-old child prodigy Bobby Fischer made a pair of remarkably creative moves against grandmaster Donald Byrne. First he sacrificed his knight, seemingly for no gain, and then exposed his queen to capture. On the surface, these moves seemed insane, but several moves later, Fischer used these moves to win the game. His creativity was hailed at the time as the mark of genius. Yet today if you program that same position into a run-of-the-mill chess program, it will immediately suggest exactly the moves that Fischer played. It’s not because the computer has memorized the Fischer–Byrne game, but rather because it searches far enough ahead to see that these moves really do pay off. Sometimes, one man’s creativity is another machine’s brute-force analysis.
²²

We’re very confident that more surprises are in store. After spending time working with leading technologists and watching one bastion of human uniqueness after another fall before the inexorable onslaught of innovation, it’s becoming harder and harder to have confidence that any given task will be indefinitely resistant to automation. That means people will need to be more adaptable and flexible in their career aspirations, ready to move on from areas that become subject to automation, and seize new opportunities where machines complement and augment human capabilities. Maybe we’ll see a program that can scan the business landscape, spot an opportunity, and write up a business plan so good it’ll have venture capitalists ready to invest. Maybe we’ll see a computer that can write a thoughtful and insightful report on a complicated topic. Maybe we’ll see an automatic medical diagnostician with all the different kinds of knowledge and awareness of a human doctor. And maybe we’ll see a computer than can walk up the stairs to an elderly woman’s apartment, take her blood pressure, draw blood, and ask if she’s been taking her medication, all while putting her at ease instead of terrifying her. We don’t think any of these advances is likely to come any time soon, but we’ve also learned that it’s very easy to underestimate the power of digital, exponential, and combinatorial innovation. So never say never.

“A policy is a temporary creed liable to be changed, but while it holds good it has got to be pursued with apostolic zeal.”

—Mahatma Gandhi

W
HAT
SHOULD
WE
DO
to encourage the bounty of the second machine age while working to reduce the spread, or at least mitigate its harmful effects? How can we best encourage technology to race ahead while ensuring that as few people as possible are left behind?

With so much science-fiction technology becoming reality now every day, it might seem that radical steps are necessary. But this is not the case, at least not right away. Many of the recommendations for growth and prosperity found in just about any standard “Economics 101” textbook are the right place to start and will be for some time to come. In our discussions with policy makers, technologists, and business executives, we were surprised to find that the logic behind these recommendations was often not well understood. Hence this chapter.

A Few Things Even Economists Can Agree On

The standard Econ 101 textbook still provides the right playbook these days because despite recent advances, digital labor is still far from a complete substitute for human labor. Robots and computers, as powerful and capable as they are, are not about to take all of our jobs. Google’s autonomous car can’t yet drive on all roads or in all conditions, and it doesn’t know what to do when a flagman or traffic cop appears in the middle of the street to manually direct traffic. (That’s not to suggest the car would keep driving and run this person over; it would stop and wait for the situation to normalize.) The technologies that make Watson so potent are being applied in many fields, including health care, finance, and customer service, but for now the system is still just a really good
Jeopardy!
player.

In the short term, companies will still need human workers to satisfy their customers and succeed in the economy. (We’ll discuss the longer term in the next chapter). Yes, second-machine-age technologies are quickly leaving the lab and entering mainstream business. But as rapid as this progress is, we still have lots of human cashiers, customer service representatives, lawyers, drivers, policemen, home health aides, managers, and other workers. They are not all on the brink of being swept out of their jobs by a cresting wave of computerization. In March 2013 the U.S. workforce consisted of over 142 million people; in each case, their employers chose them over digital technologies (or in addition to them) even after more than fifty years of experience and improvement with business computers, thirty years with PCs, and almost twenty with the World Wide Web.
¹
While those employers are likely to choose digital labor more often in the future, it will not be immediate and it will not be in all cases.

For now the best way to tackle our labor force challenges is to grow the economy. As companies see opportunities for growth, the great majority will need to hire people to seize them. Job growth will improve, and so will workers’ prospects.

If only growth were that easy. Fierce debates rage about the best ways to bring about faster economic expansion. In particular, there are long-standing and deep disagreements about the proper role of government in this area. Economists, policy makers, and businesspeople alike argue questions of monetary policy—Should the Federal Reserve increase the money supply? What interest should it charge banks?—and fiscal policy—How should the government spend the money it raises? How much debt should it take on? What’s the right level and mix of income, sales, corporate, and other taxes? What should the top tax rate be?

Disagreements over these questions often seem so entrenched that there can be no common ground. But there’s actually quite a bit of it. Whether you study from the best-selling introductory textbooks
Principles of Economics
, written by Harvard’s Greg Mankiw, a conservative economist who advised George Bush and Mitt Romney, or
Economics: An Introductory Analysis
, written by MIT’s Paul Samuelson, a liberal advisor to John Kennedy and Lyndon B. Johnson, you’ll learn many of the same things.
*
Across good Econ 101 textbooks, and across good economists, there’s far more agreement about government’s role in promoting economic growth than you might expect from the more vitriolic public debates in the media. We agree with this Econ 101 playbook as well, and think it will remain central to any appropriate response as machines continue to race ahead.

This playbook advocates government policies and other interventions in a few key areas. Not all of them are concerned with the digital tools of the second machine age. This is because many of the things we should do in a time of brilliant technologies are not related to the technologies themselves. Instead, they’re about promoting economic growth and opportunity more generally. Here’s our Econ 101 playbook on how to do that.

1. Teach The Children Well

The United States was the clear leader in primary education in the first half of the twentieth century, having realized that inequality was a “race between education and technology,” to use a phrase coined by Jan Tinbergen (winner of the first Nobel Prize in Economic Sciences) and used by the economists Claudia Goldin and Lawrence Katz as the title of their influential 2010 book.
²
When technology advances too quickly for education to keep up, inequality generally rises. Realizing this early last century, the United States made substantial investments in primary education. Goldin documents that by 1955, for example, almost 80 percent of American children between the ages of fifteen and nineteen were enrolled in high schools, a level more than twice as high as that in any European country at the time.

Over the past half century that strong U.S. advantage in primary education has vanished, and the country is now no better than the middle of the pack among wealthy countries, and worse in some important areas. The most recent survey by the Organization for Economic Co-operation and Development’s (OECD) Program for International Student Assessment (PISA), conducted in 2009, found that American fifteen-year-olds ranked fourteenth among the thirty-four countries in reading, seventeeth in science, and twenty-fifth in math.
³
As education researcher Martin West summarizes, “In math, the average U.S. student by age 15 was at least a full year behind the average student in six countries, including Canada, Japan, and the Netherlands. Students in six additional countries, including Australia, Belgium, Estonia, and Germany, outperformed U.S. students by more than half a year.”
⁴

The economic benefits of closing that gap are likely to be quite large. The economists Eric Hanushek and Ludger Woessmann found a strong relationship between improved test scores and faster economic growth after studying forty years’ worth of data from fifty countries. This suggests that if the United States could move its students to the top of the international rankings, it might enjoy a substantial boost in GDP growth, especially since many of the country’s products and services rely heavily on skilled labor. What’s more, it’s not an accident that the most educated places in the country, like Austin, Texas; Boston; Minneapolis; and San Francisco have low unemployment rates.

It’s been said that America’s greatest idea was mass education. It’s still a great idea that applies at all levels, not just K-12 and university education, but also preschool, vocational, and lifelong learning.

So, how can we get better results?

USING TECHNOLOGY

We can change the way we deliver education by putting to work digital technologies that have been developed over the past decade or two. The good news is that compared to other industries such as media, retailing, finance, or manufacturing, education is a tremendous laggard in the use of technology. That’s good news because it means we can expect big gains simply by catching up to other industries. Innovators can make a huge difference in this area in the coming decade.

The tremendous experimentation now underway with massive online open courses, or MOOCs, is especially encouraging. We discussed MOOCs, which anyone can take, often for free, in some detail in the previous chapter on recommendations for individuals. But we want to point out two of their main economic benefits.